Search Results - (( regional distribution factor algorithm ) OR ( based evaluation means algorithm ))
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1
Model-based hybrid variational level set method applied to object detection in grey scale images
Published 2024“…To tackle the persistent challenge of segmenting grayscale images with both uneven characteristics and high noise levels, a hybrid level-set algorithm based on kernel metrics is introduced. This algorithm leverages an improved multi-scale mean filter to mitigate grayscale inhomogeneity while reducing the impact of scale parameter selection. …”
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Thesis -
2
Termite mounds morphometry in predicting groundwater potentiality using geospatial technology
Published 2020“…The effects of five (5) environmental factors (elevation, land use/land cover, geology, drainage and static water level) on the distribution of termite mounds as well as their structure, mortality rate and species diversity formed a knowledge-base for multi-criteria evaluation of suitable sites for termite nesting. …”
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3
Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…Adopting the medoid instead of the mean can enhance the efficiency. However, the complexity of the kmedoid based algorithms in general is more than the complexity of the k-means based algorithms. …”
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4
A study on regional GDP forecasting analysis based on radial basis function neural network with genetic algorithm (RBFNN-GA) for Shandong economy
Published 2022“…These basic indicators can comprehensively and effectively reflect a country’s or region’s future economic development. The center of radial basis function neural network and smoothing factor to take a uniform distribution of the random radial basis function artificial neural network will be the focus of this study. …”
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5
Determination of dengue hemorrhagic fever disease factors using neural network and genetic algorithms / Yuliant Sibaroni, Sri Suryani Prasetiyowati and Iqbal Bahari Sudrajat
Published 2020“…This experiment show that the main factors that influence the spread of DHF in Bandung area are temperature, altitude, distribution of gender, and distribution of education levels. …”
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6
Objective and Subjective Evaluations of Adaptive Noise Cancellation Systems with Selectable Algorithms for Speech Intelligibility
Published 2018“…For subjective evaluation, listening tests were evaluated using the Mean Opinion Score (MOS) technique. …”
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An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis
Published 2022“…The objective of this paper is to investigate how the parameters behave with a measurement criterion for feature selection, that is, the total error reduction ratio (TERR). The k-means and the Gaussian mixture distribution were adopted as the clustering algorithms and each algorithm was tested on four datasets with four distinct clustering evaluation criteria: Calinski-Harabasz, Davies-Bouldin, Gap and Silhouette. …”
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Book Chapter -
8
Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network
Published 2023“…The evaluation process was implemented on RK-Means, K-Means++, and OK-Means models. …”
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9
Chlorophyll-A concentration mapping in northern region of peninsular Malaysia waters / Nur Syuhada Aijimi
Published 2019“…Monitoring the chlorophyll concentration and distribution especially for large area such as Northern Region of Peninsular Malaysia Waters using remote sensing technique which is by satellite image' extraction using specific algorithms can map the trend changes of fish distribution and can know the effect of climatic factors such as changes in sea surface temperatures to the chlorophyll concentration. …”
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10
Performance evaluation of different data aggregation algorithms for different types of sensors in WSN based cluster
Published 2018“…The algorithms applied separately with (1) Mean (2) Median (3) Mode (4) Geometric mean (5) Harmonic mean. …”
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11
Image segmentation based on normalised cuts with clustering algorithm
Published 2013“…Evaluation of c -means and fuzzy c-means clustering algorithm with normalised cuts image segmentation on various kinds of images has been carried out. …”
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12
Comparison of performance and computational complexity of nonlinear active noise control algorithms
Published 2011“…The evaluation of the algorithms performance is standardized in terms of the normalized mean square error while the computational complexity is calculated based on the number of multiplications and additions in a single iteration. …”
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13
Document clustering based on firefly algorithm
Published 2015“…Document clustering is widely used in Information Retrieval however, existing clustering techniques suffer from local optima problem in determining the k number of clusters.Various efforts have been put to address such drawback and this includes the utilization of swarm-based algorithms such as particle swarm optimization and Ant Colony Optimization.This study explores the adaptation of another swarm algorithm which is the Firefly Algorithm (FA) in text clustering.We present two variants of FA; Weight- based Firefly Algorithm (WFA) and Weight-based Firefly Algorithm II (WFAII).The difference between the two algorithms is that the WFAII, includes a more restricted condition in determining members of a cluster.The proposed FA methods are later evaluated using the 20Newsgroups dataset.Experimental results on the quality of clustering between the two FA variants are presented and are later compared against the one produced by particle swarm optimization, K-means and the hybrid of FA and -K-means. …”
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14
Segmentation of MRI brain images using statistical approaches
Published 2011“…Noise is one of the obstacles for brain MRI segmentation. The non-Local means (NL-means) algorithm is a state-of-the art neighbourhood-based noisereduction method which is time-consuming and its accuracy can be improved. …”
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Centre-based hard clustering algorithms for Y-STR data / Ali Seman, Zainab Abu Bakar and Azizian Mohd. Sapawi
Published 2010“…The k-Means and the k-Modes algorithms are the fundamental algorithms for the centroid-based partitioning technique, whereas the k-Medoids is a representative object-based partitioning technique. …”
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17
Support Vector Machines (SVM) in Test Extraction
Published 2006“…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. …”
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Final Year Project -
18
Support Vector Machines (SVM) in Test Extraction
Published 2006“…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. …”
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Final Year Project -
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FACTORS INFLUENCING THE INTENTION TO ADOPT E-WALLET: A REGIONAL DISTRIBUTION PERSPECTIVE IN MALAYSIA
Published 2022“…Besides, a regional distribution, and the mediating effect of perceived trust between knowledge and intention to adopt e-wallet is examined. …”
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20
Eye-state analysis using an interdependence and adaptive scale mean shift (IASMS) algorithm
Published 2014“…This paper presents a novel eye state analysis design aimed for human fatigue evaluation systems. The design is based on an interdependence and adaptive scale mean shift (IASMS) algorithm. …”
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